Jeff’s career is storied and diverse. He’s built systems to protect the gambling industry from card counters, technology that allows organization’s to collect and analyze personally identifiable information without invading personal privacy and ways to make sense of data as it happens.

In this exclusive interview, sponsored by IBM, Jeff talks about pulling useful business intelligence from big data, comparing data points, why big data improves the accuracy of predictions, helping casino operators bring down the MIT Blackjack Team with data, the value of automated trading algorithms to Goldman Sachs, how Watson uses contradictory information to eliminate false positives, the shortcomings of pulling meaningful KPIs from social media monitoring services and sentiment analytics alone, the Fair Credit Reporting Act, why insufficient an observation space leads to fantasy analytics, the future of secrets and the importance of corporate training and business process improvement.